Wells Fargo
Financial Services
PrincipalEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Principal Engineer at Wells Fargo. Skills: Agentic AI, Microsoft 365 Copilot, Copilot Studio, Copilot Cowork. Provide technical leadership for AI capabilities. Define architecture and engineering standards”
Industry & Context.
Resolve challenges; Resolve roadblocks; Problem solving
What They're Looking For.
Must Have
7+ years Engineering experience
Nice to Have
Generative AI production experience, Agentic AI production experience, Microsoft 365 Copilot extensibility expertise, Copilot Studio experience, Copilot Cowork experience, AI capabilities across OS platforms, Grounding agents over enterprise data, API and microservices design, Containerization experience, CI/CD experience, DevSecOps experience, Automated testing experience, Responsible AI principles application, Senior technical leader experience, AI capabilities in regulated environment
What You'll Do.
Provide technical leadership for AI capabilities
Define architecture and engineering standards
Design and build end-to-end agentic solutions
Lead delivery of agents and automations
Establish reusable patterns
Define how agents are extended
cross-application workflows
Drive complex technical initiatives
Resolve ambiguous architecture challenges
Set and enforce engineering best practices
Embed responsible AI into engineering
Partner with architects and leadership
Shape next generation domain architecture
Conduct deep technical design reviews
Contribute hands-on in codebase
Serve as technical representative
Influence technology requirements and priorities
Identify and drive resolution of roadblocks
Mentor and grow senior engineers
Raise team's depth in extensibility
Interact with technology partners
Advance Copilot platform capabilities
Interpret and develop AI capabilities
Set engineering standards and patterns
Enable teams to build agents
Drive resolution of technical problems
Remain hands-on in codebase
Embed responsible AI into foundation
Influence architecture and roadmap
Partner with leadership on direction
Elevate technical depth of organization
How You'll Work.
Team & Collaboration
Cross-team planning; Collaborative efforts; Partner with architects; Partner with leadership; Interact with partners
Communication Scope
Technical reviews; Peer reviews; Presentations
Process & Methodology
Roadmap planning
Full Job Description
**About this role:** Wells Fargo is seeking a Principal Engineer to provide deep technical leadership for AI capabilities across Microsoft 365 and OS platforms, with a focus on the design and delivery of agentic AI solutions and workflows built on Microsoft 365 Copilot, Copilot Studio, and Copilot Cowork. As the most senior individual contributor on the team, you will define how agents, skills, and plug-ins are built, secured, and scaled across the enterprise — turning the Copilot platform into intelligent, autonomous experiences for the workforce. ****In this role, you will:**** * Act as the principal technical authority for agentic AI across Microsoft 365 (Teams, Outlook, SharePoint, Graph, Copilot) and OS platforms (Windows, macOS, iOS, Android), defining architecture and engineering standards for agents, skills, plug-ins, and AI-driven workflows * Design and build end-to-end agentic solutions on the Microsoft 365 Copilot platform — declarative and custom agents, skills composition, plug-in/tool calling, grounding over enterprise data via Microsoft Graph, and multi-step autonomous workflows * Lead delivery of agents and automations in Copilot Studio and Copilot Cowork, establishing reusable patterns, skills libraries, and plug-in frameworks that other teams build on * Define how Copilot Cowork agents are extended with custom skills and plug-ins to automate complex, cross-application workplace workflows securely and reliably * Drive the most complex, highest-risk technical initiatives across teams, resolving ambiguous architecture and integration challenges spanning the Copilot platform, Microsoft Graph, and OS extensibility points * Set and enforce engineering best practices for agentic AI delivery — agent and skill evaluation, prompt and skill versioning, observability, latency and cost optimization, CI/CD, and automated testing for non-deterministic AI systems * Embed responsible AI into the engineering foundation: grounding, safety, guardrails, data privacy, m
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